Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10403602 | IFAC Proceedings Volumes | 2005 | 6 Pages |
Abstract
In this paper a nonlinear system identification methodology based on a polynomial NARMAX model representation is considered. Algorithms for structure selection and parameter estimation are presented and evaluated. The goal of the procedure is to provide a nonlinear model characterized by a low complexity and that can be efficiently used in industrial applications. The methodology is illustrated by means of an automotive case study namely a variable geometry turbocharged diesel engine. The nonlinear model representing the relation between the variable geometry turbine command and the intake manifold air pressure is identified from data and validated.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Gianluca Zito, Ioan Doré Landau,